Integrating diabetes pathophysiology from genotype to phenotype in whole genome sequence association studies of glycemic traits. Type 2 diabetes (T2D) and glycemic traits such as fasting glucose (FG) and fasting insulin (FI) levels are influenced by environmental, physiological and genetic factors. Genome-wide association studies (GWAS) show that the non-coding genome harbors most of the common alleles associated with T2D, FG and FI. The goal of this project is to thoroughly explore non-coding genetic variation functionally linked to insulin signaling (IS) and glucose homeostasis (GH). These studies are motivated by recent rare coding variants associated with FI and FG that have been found in IS and GH pathways. In this project, methods are proposed that increase the efficiency of whole genome sequence association studies (WGSAS) to discover rare non-coding glycemic trait associations. A hypothesis explored is that power of WGSAS can be increased by: (a) prioritizing regions of the genome functionally linked to IS and GH genes, and (b) testing associations using trait transformations and covariate adjustments that increase phenotype homogeneity will result in larger genetic effects. This program will accomplish these goals with the following Specific Aims. Aim 1: To prioritize target regions, annotations will be applied to th genome with non-coding functional elements identified from metabolic tissues involved in IS and GH and examine enrichment of glycemic trait associations in all the functional elements and in elements linked to genes in IS and GH pathways. Aim 2: To address phenotype heterogeneity, refined phenotype models will be derived using both insight from monogenic disorders and phenotypic and genetic links between insulin resistance, adiposity, environmental exposures, metabolic health, and T2D. Aim 3: To find new, rare non-coding alleles associated with glycemic traits, a statistical framework will be developed that integrates the target regions from Aim 1 wit the derived phenotypes from Aim 2 and apply this framework to the data sets in the T2D-GENES, GoT2D and CHARGE consortia. These aims integrate diabetes pathophysiology from genotype to phenotype, reflect a carefully planned training program, and will lead to research independence and R01 proposals for functional follow-up of the non-coding alleles variants discovered in Aim 3 with cell types and molecular phenotype assays informed by Aim 1 and Aim 2. The Principle Investigator, Dr. Alisa K, Manning, Ph.D., is an early career statistical geneticit with an established focus on glycemic traits and experience developing statistical methods for genetic association studies. To develop into an independent researcher, she requires additional training in regulatory genomics and the physiology of glucose regulation. If successful, this could provide new drug targets to treat or prevent type 2 diabetes. Furthermore, these integrative methods and results will be used to illuminate the genetic architecture of T2D for rare alleles across the genome, leading to a better understanding of T2D etiology.